DBMS > 4D vs. FatDB vs. HugeGraph

System Properties Comparison 4D vs. FatDB vs. HugeGraph

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

Application development environment with integrated database management system

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

A fast-speed and highly-scalable Graph DBMS

Primary database model

Relational DBMS

Document store
Key-value store

Graph DBMS

DB-Engines Ranking measures the popularity of database management systems
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Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Website

www.4d.com

github.com/hugegraph
hugegraph.apache.org

Technical documentation

developer.4d.com

hugegraph.apache.org/docs

Developer

4D, Inc

FatCloud

Baidu

Initial release

1984

2012

2018

Current release

v20, April 2023

0.9

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

OS X
Windows

Windows

Linux
macOS
Unix

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

also supports composite index and range index

SQL

Support of SQL

yes

close to SQL 92

Via inetgration in SQL Server

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

Java API
RESTful HTTP API
TinkerPop Gremlin

Supported programming languages

4D proprietary IDE
PHP

Groovy
Java
Python

Server-side scripts

Stored procedures

yes

via applications

asynchronous Gremlin script jobs

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

yes

depending on used storage backend, e.g. Cassandra and HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

edges in graph

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Users and groups

Can implement custom security layer via applications

Users, roles and permissions

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More resources

DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

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Recent citations in the news

Critical Apache HugeGraph Flaw Let Attackers Execute Remote Code
23 April 2024, GBHackers

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